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Title: Evolutionary Diversity Peaks at Mid-Elevations Along an Amazon-to-Andes Elevation Gradient
Elevation gradients present enigmatic diversity patterns, with trends often dependent on the dimension of diversity considered. However, focus is often on patterns of taxonomic diversity and interactions between diversity gradients and evolutionary factors, such as lineage age, are poorly understood. We combine forest census data with a genus level phylogeny representing tree ferns, gymnosperms, angiosperms, and an evolutionary depth of 382 million years, to investigate taxonomic and evolutionary diversity patterns across a long tropical montane forest elevation gradient on the Amazonian flank of the Peruvian Andes. We find that evolutionary diversity peaks at mid-elevations and contrasts with taxonomic richness, which is invariant from low to mid-elevation, but then decreases with elevation. We suggest that this trend interacts with variation in the evolutionary ages of lineages across elevation, with contrasting distribution trends between younger and older lineages. For example, while 53% of young lineages (originated by 10 million years ago) occur only below ∼1,750 m asl, just 13% of old lineages (originated by 110 million years ago) are restricted to below ∼1,750 m asl. Overall our results support an Environmental Crossroads hypothesis, whereby a mid-gradient mingling of distinct floras creates an evolutionary diversity in mid-elevation Andean forests that rivals that of the Amazonian lowlands.  more » « less
Award ID(s):
1754647
NSF-PAR ID:
10348196
Author(s) / Creator(s):
; ; ; ; ; ; ; ;
Date Published:
Journal Name:
Frontiers in Ecology and Evolution
Volume:
9
ISSN:
2296-701X
Format(s):
Medium: X
Sponsoring Org:
National Science Foundation
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We also used the Tukey–Kramer method to compare the frequency distributions of TDP concentrations in all of the soil leachate samples with concentrations in lakes, streams, and groundwater wells, since each sample category had very different numbers of measurements. Individual spreadsheets in “data table_leaching_dissolved organic carbon and nitrogen.xls” 1.    annual precip_drainage 2.    biomass_corn, perennial grasses 3.    biomass_poplar 4.    annual N leaching _vol-wtd conc 5.    Summary_N leached 6.    annual DOC leachin_vol-wtd conc 7.    growing season length 8.    correlation_nh4 VS no3 9.    correlations_don VS no3_doc VS don Each spreadsheet is described below along with an explanation of variates. Note that ‘nan’ indicate data are missing or not available. First row indicates header; second row indicates units 1. Spreadsheet: annual precip_drainage Description: Precipitation measured from nearby Kellogg Biological Station (KBS) Long Term Ecological Research (LTER) Weather station, over 2009-2016 study period. Data shown in Figure 1; original data source for precipitation (https://lter.kbs.msu.edu/datatables/7). Drainage estimated from SALUS crop model. Note that drainage is percolation out of the root zone (0-125 cm). Annual precipitation and drainage values shown here are calculated for growing and non-growing crop periods. Variate    Description year    year of the observation crop    “corn” “switchgrass” “miscanthus” “nativegrass” “restored prairie” “poplar” precip_G    precipitation during growing period (milliMeter) precip_NG    precipitation during non-growing period (milliMeter) drainage_G    drainage during growing period (milliMeter) drainage_NG    drainage during non-growing period (milliMeter)      2. Spreadsheet: biomass_corn, perennial grasses Description: Maximum aboveground biomass measurements from corn, switchgrass, miscanthus, native grass and restored prairie plots in Great Lakes Bioenergy Research Center (GLBRC) Biomass Cropping System Experiment (BCSE) during 2009-2015. Data shown in Figure 2.   Variate    Description year    year of the observation date    day of the observation (mm/dd/yyyy) crop    “corn” “switchgrass” “miscanthus” “nativegrass” “restored prairie” “poplar” replicate    each crop has four replicated plots, R1, R2, R3 and R4 station    stations (S1, S2 and S3) of samplings within the plot. For more details, refer to link (https://data.sustainability.glbrc.org/protocols/156) species    plant species that are rooted within the quadrat during the time of maximum biomass harvest. See protocol for more information, refer to link (http://lter.kbs.msu.edu/datatables/36) For maize biomass, grain and whole biomass reported in the paper (weed biomass or surface litter are excluded). Surface litter biomass not included in any crops; weed biomass not included in switchgrass and miscanthus, but included in grass mixture and prairie. fraction    Fraction of biomass biomass_plot    biomass per plot on dry-weight basis (Grams_Per_SquareMeter) biomass_ha    biomass (megaGrams_Per_Hectare) by multiplying column biomass per plot with 0.01 3. Spreadsheet: biomass_poplar Description: Maximum aboveground biomass measurements from poplar plots in Great Lakes Bioenergy Research Center (GLBRC) Biomass Cropping System Experiment (BCSE) during 2009-2015. Data shown in Figure 2. Note that poplar biomass was estimated from crop growth curves until the poplar was harvested in the winter of 2013-14. Variate    Description year    year of the observation method    methods of poplar biomass sampling date    day of the observation (mm/dd/yyyy) replicate    each crop has four replicated plots, R1, R2, R3 and R4 diameter_at_ground    poplar diameter (milliMeter) at the ground diameter_at_15cm    poplar diameter (milliMeter) at 15 cm height biomass_tree    biomass per plot (Grams_Per_Tree) biomass_ha    biomass (megaGrams_Per_Hectare) by multiplying biomass per tree with 0.01 4. Spreadsheet: annual N leaching_vol-wtd conc Description: Annual leaching rate (kiloGrams_N_Per_Hectare) and volume-weighted mean N concentrations (milliGrams_N_Per_Liter) of nitrate (no3) and dissolved organic nitrogen (don) in the leachate samples collected from corn, switchgrass, miscanthus, native grass, restored prairie and poplar plots in Great Lakes Bioenergy Research Center (GLBRC) Biomass Cropping System Experiment (BCSE) during 2009-2016. Data for nitrogen leached and volume-wtd mean N concentration shown in Figure 3a and Figure 3b, respectively. Note that ammonium (nh4) concentration were much lower and often undetectable (<0.07 milliGrams_N_Per_Liter). Also note that in 2009 and 2010 crop-years, data from some replicates are missing.    Variate    Description crop    “corn” “switchgrass” “miscanthus” “nativegrass” “restored prairie” “poplar” crop-year    year of the observation replicate    each crop has four replicated plots, R1, R2, R3 and R4 no3 leached    annual leaching rates of nitrate (kiloGrams_N_Per_Hectare) don leached    annual leaching rates of don (kiloGrams_N_Per_Hectare) vol-wtd no3 conc.    Volume-weighted mean no3 concentration (milliGrams_N_Per_Liter) vol-wtd don conc.    Volume-weighted mean don concentration (milliGrams_N_Per_Liter) 5. Spreadsheet: summary_N leached Description: Summary of total amount and forms of N leached (kiloGrams_N_Per_Hectare) and the percent of applied N lost to leaching over the seven years for corn, switchgrass, miscanthus, native grass, restored prairie and poplar plots in Great Lakes Bioenergy Research Center (GLBRC) Biomass Cropping System Experiment (BCSE) during 2009-2016. Data for nitrogen amount leached shown in Figure 4a and percent of applied N lost shown in Figure 4b. Note the fraction of unleached N includes in harvest, accumulation in root biomass, soil organic matter or gaseous N emissions were not measured in the study. Variate    Description crop    “corn” “switchgrass” “miscanthus” “nativegrass” “restored prairie” “poplar” no3 leached    annual leaching rates of nitrate (kiloGrams_N_Per_Hectare) don leached    annual leaching rates of don (kiloGrams_N_Per_Hectare) N unleached    N unleached (kiloGrams_N_Per_Hectare) in other sources are not studied % of N applied N lost to leaching    % of N applied N lost to leaching 6. Spreadsheet: annual DOC leachin_vol-wtd conc Description: Annual leaching rate (kiloGrams_Per_Hectare) and volume-weighted mean N concentrations (milliGrams_Per_Liter) of dissolved organic carbon (DOC) in the leachate samples collected from corn, switchgrass, miscanthus, native grass, restored prairie and poplar plots in Great Lakes Bioenergy Research Center (GLBRC) Biomass Cropping System Experiment (BCSE) during 2009-2016. Data for DOC leached and volume-wtd mean DOC concentration shown in Figure 5a and Figure 5b, respectively. Note that in 2009 and 2010 crop-years, water samples were not available for DOC measurements.     Variate    Description crop    “corn” “switchgrass” “miscanthus” “nativegrass” “restored prairie” “poplar” crop-year    year of the observation replicate    each crop has four replicated plots, R1, R2, R3 and R4 doc leached    annual leaching rates of nitrate (kiloGrams_Per_Hectare) vol-wtd doc conc.    volume-weighted mean doc concentration (milliGrams_Per_Liter) 7. Spreadsheet: growing season length Description: Growing season length (days) of corn, switchgrass, miscanthus, native grass, restored prairie and poplar plots in the Great Lakes Bioenergy Research Center (GLBRC) Biomass Cropping System Experiment (BCSE) during 2009-2015. Date shown in Figure S2. Note that growing season is from the date of planting or emergence to the date of harvest (or leaf senescence in case of poplar).   Variate    Description crop    “corn” “switchgrass” “miscanthus” “nativegrass” “restored prairie” “poplar” year    year of the observation growing season length    growing season length (days) 8. Spreadsheet: correlation_nh4 VS no3 Description: Correlation of ammonium (nh4+) and nitrate (no3-) concentrations (milliGrams_N_Per_Liter) in the leachate samples from corn, switchgrass, miscanthus, native grass, restored prairie and poplar plots in Great Lakes Bioenergy Research Center (GLBRC) Biomass Cropping System Experiment (BCSE) during 2013-2015. Data shown in Figure S3. Note that nh4+ concentration in the leachates was very low compared to no3- and don concentration and often undetectable in three crop-years (2013-2015) when measurements are available. Variate    Description crop    “corn” “switchgrass” “miscanthus” “nativegrass” “restored prairie” “poplar” date    date of the observation (mm/dd/yyyy) replicate    each crop has four replicated plots, R1, R2, R3 and R4 nh4 conc    nh4 concentration (milliGrams_N_Per_Liter) no3 conc    no3 concentration (milliGrams_N_Per_Liter)   9. Spreadsheet: correlations_don VS no3_doc VS don Description: Correlations of don and nitrate concentrations (milliGrams_N_Per_Liter); and doc (milliGrams_Per_Liter) and don concentrations (milliGrams_N_Per_Liter) in the leachate samples of corn, switchgrass, miscanthus, native grass, restored prairie and poplar plots in Great Lakes Bioenergy Research Center (GLBRC) Biomass Cropping System Experiment (BCSE) during 2013-2015. Data of correlation of don and nitrate concentrations shown in Figure S4 a and doc and don concentrations shown in Figure S4 b. Variate    Description crop    “corn” “switchgrass” “miscanthus” “nativegrass” “restored prairie” “poplar” year    year of the observation don    don concentration (milliGrams_N_Per_Liter) no3     no3 concentration (milliGrams_N_Per_Liter) doc    doc concentration (milliGrams_Per_Liter) 
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  3. Abstract

    Geographically, widespread Neotropical fish lineages offer opportunities to reconstruct historical biogeography patterns and infer processes leading to modern ichthyological diversity and distribution. The characiform family Prochilodontidae is well suited for such reconstruction because their migrations limit population substructure within river systems. Therefore, their biogeographic history should match closely the history of connectivity among Neotropical river basins. Here, we combine a time‐calibrated phylogeny with biogeographic model testing to recover the history of this family's diversification. Results support the Miocene rise of the Andean Eastern Cordillera as a dispersal barrier, but also indicate a much earlier Eocene origin of the trans‐Andean genusIchthyoelephas. Despite the early origin of the family and its three constituent genera, most prochilodontid lineages originated during the Miocene in Greater Amazonia, likely due to drainage reorganizations caused by Andean uplift. Subsequent speciation appears linked to interbasin exchanges and expansions of Amazonian lineages into Brazilian coastal systems. The modern richness ofProchilodusin easterly drainages appears to be relatively young, with onlyProchilodus vimboideslikely reaching that region prior to the late Miocene. The rise of the Vaupes Arch coincides with two splits between Orinocoan and Amazonian lineagescirca9 million years ago (Ma). However, two instances of later dispersal between these drainages reveal the permeability of the Vaupes Arch, suggesting that it may promote periodic speciation. This study illustrates how model‐based biogeographic studies of widespread groups can reconstruct historic paths of dispersal and help reveal how landscape evolution promoted modern diversity patterns.

     
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  4. Abstract Aim

    Mountains provide uniquely informative systems for examining how biodiversity is distributed and identifying the causes of those patterns. Elevational patterns of species richness are well‐documented for many taxa but comparatively few studies have investigated patterns in multiple dimensions of biodiversity along mountainsides, which can reveal the underlying processes at play. Here, we use trait‐based diversity patterns to determine the role of abiotic filters and competition in the assembly of communities of small mammals across elevation and evaluate the surrogacy of taxonomic, functional, and phylogenetic dimensions of diversity.

    Location

    Great Basin ecoregion, western North America.

    Taxon

    Rodents and shrews.

    Methods

    The elevational distributions of 34 species were determined from comprehensive field surveys conducted in three arid, temperate mountain ranges. Elevation–diversity relationships and community assembly processes were inferred from phylogenetic (PD) and functional diversity (FD) patterns of mean pairwise and mean nearest‐neighbor distances while accounting for differences in species richness. FD indices were calculated separately for traits related to either abiotic filtering (β‐niche traits) or biotic interactions (α‐niche traits) to test explicit predictions of the role of each across elevation.

    Results

    Trait‐based tests of processes indicated that abiotic filtering tied to a strong aridity gradient drives the assembly of both low‐ and high‐elevation communities. Support for competition was not consistent with theoretical expectations under the stress‐dominance hypothesis, species interactions‐abiotic stress hypothesis, or guild assembly rule. Mid‐elevation peaks in species richness contrasted with overall FD and PD, which generally increased with elevation. PD and total FD were correlated on two of three mountains.

    Main conclusions

    The functional diversity of small mammal communities in these arid, temperate mountains is most consistent with abiotic filters, whereas support for competition is weak. Decomposing FD into traits related to separate assembly processes and examining ecoregional variation in diversity were critical for uncovering the generality of mechanisms. Divergent patterns among dimensions revealed species richness to be a poor surrogate for PD and FD across elevation and reflect the effect of biogeographic and evolutionary history. This first analysis of elevational multidimensional diversity gradients for temperate mammals provides a versatile framework for future comparative studies.

     
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